We were involved in the EU FP7 project OpenTox. The overall objective of the project was to develop a framework that provides a unified access to toxicity data, (Q)SAR models, procedures supporting validation and additional information that helps with the interpretation of (Q)SAR predictions. The OpenTox framework has been developed as an open source project to optimize the dissemination and impact, to allow the inspection and review of algorithms and to attract external contributors. We closely collaborated with related projects (e.g. OECD toolbox) and authorities to agree on common standards and to avoid duplicated and redundant work. The project was very international with partners from Switzerland, Bulgaria, Italy, Greece, Russia, India, USA and Germany. The partners are from academic, government and economic background. Additionally, the project had an advisory board with members from government organizations and industry. As a work package leader, TUM was responsible for the selection and development of (Q)SAR algorithms for predictive toxicology.
Girschick, T, Buchwald, F, Hardy, B, and Kramer, S
OpenTox: A Distributed REST Approach to Predictive Toxicology
In: Proceedings of the 3rd Workshop on Third-Generation Data Mining: Towards Service-Oriented Knowledge Discovery (SoKD’10) at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2010, ed. by Melanie Hilario, Nada Lavrač, Vid Podpečan, Joost N. Kok, pp. 61-62.